Skin cancer recognition by computer vision
Automatic detection of several features characteristic of basal cell epitheliomas is described. The features selected for this feasibility study are semitranslucency, telangiectasia, ulcer, crust, and tumor border. Image processing methods used in this study include frequency analysis of the Fourier...
Gespeichert in:
| Veröffentlicht in: | Computerized medical imaging and graphics 1989, Vol.13 (1), p.31-36 |
|---|---|
| Hauptverfasser: | , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 36 |
|---|---|
| container_issue | 1 |
| container_start_page | 31 |
| container_title | Computerized medical imaging and graphics |
| container_volume | 13 |
| creator | Moss, Randy H. Stoecker, William V. Lin, Shi-Jen Muruganandhan, Sundararajun Chu, Kuang-Fu Poneleit, Kathy M. Mitchell, Carl D. |
| description | Automatic detection of several features characteristic of basal cell epitheliomas is described. The features selected for this feasibility study are semitranslucency, telangiectasia, ulcer, crust, and tumor border. Image processing methods used in this study include frequency analysis of the Fourier transform of the image, the Sun-Wee texture analysis algorithm, and several other image analysis techniques suitable for skin photographs. This image analysis software is designed for use with AI/DERM, an expert system that models diagnosis of skin tumors by dermatologists. |
| doi_str_mv | 10.1016/0895-6111(89)90076-1 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_78904053</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>0895611189900761</els_id><sourcerecordid>78904053</sourcerecordid><originalsourceid>FETCH-LOGICAL-c387t-d8759a5603205673d2d05cc6da0a940605f8579d5318e9ed16188998a4581df93</originalsourceid><addsrcrecordid>eNp9kE1LAzEQhoMotVb_gcJeFBVWZ3Y3XxdBil9Q8KCeQ5pkJdru1mRb6L83tYvePA3MPPMy8xByjHCFgOwahKQ5Q8RzIS8kAGc57pAhCi5z4Bx3yfAX2ScHMX4AQAEcB2RQyKIqRDkkly-fvsmMbowLWXCmfW9859smm64z084Xyy71Vz6m1iHZq_UsuqO-jsjb_d3r-DGfPD88jW8nuSkF73IrOJWaMigLoIyXtrBAjWFWg5YVMKC1oFxaWqJw0llkKISUQldUoK1lOSJn29xFaL-WLnZq7qNxs5luXLuMigsJFdAygdUWNKGNMbhaLYKf67BWCGqjSG3-V5v_lZDqR5HCtHbS5y-nc2d_l3onaX7az3U0elaHJMfHv2zJSsCqSNzNlnNJxsq7oKLxLom0PonslG39_4d8A41Xf64</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>78904053</pqid></control><display><type>article</type><title>Skin cancer recognition by computer vision</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals Complete</source><creator>Moss, Randy H. ; Stoecker, William V. ; Lin, Shi-Jen ; Muruganandhan, Sundararajun ; Chu, Kuang-Fu ; Poneleit, Kathy M. ; Mitchell, Carl D.</creator><creatorcontrib>Moss, Randy H. ; Stoecker, William V. ; Lin, Shi-Jen ; Muruganandhan, Sundararajun ; Chu, Kuang-Fu ; Poneleit, Kathy M. ; Mitchell, Carl D.</creatorcontrib><description>Automatic detection of several features characteristic of basal cell epitheliomas is described. The features selected for this feasibility study are semitranslucency, telangiectasia, ulcer, crust, and tumor border. Image processing methods used in this study include frequency analysis of the Fourier transform of the image, the Sun-Wee texture analysis algorithm, and several other image analysis techniques suitable for skin photographs. This image analysis software is designed for use with AI/DERM, an expert system that models diagnosis of skin tumors by dermatologists.</description><identifier>ISSN: 0895-6111</identifier><identifier>EISSN: 1879-0771</identifier><identifier>DOI: 10.1016/0895-6111(89)90076-1</identifier><identifier>PMID: 2924283</identifier><language>eng</language><publisher>New York, NY: Elsevier Ltd</publisher><subject>Artificial intelligence ; Basal cell carcinoma (epithelioma) ; Biological and medical sciences ; Carcinoma, Basal Cell - diagnosis ; Computer vision ; Dermatology ; Diagnosis, Differential ; Expert Systems ; Feasibility Studies ; Fourier Analysis ; Fourier Transform processing ; Humans ; Image Interpretation, Computer-Assisted - methods ; Image processing ; Investigative techniques, diagnostic techniques (general aspects) ; Medical sciences ; Minicomputers ; Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques ; Pattern Recognition, Automated ; Photography ; Skin cancer ; Skin Neoplasms - diagnosis ; Skin Ulcer - diagnosis ; Telangiectasis - diagnosis ; Texture analysis</subject><ispartof>Computerized medical imaging and graphics, 1989, Vol.13 (1), p.31-36</ispartof><rights>1989</rights><rights>1991 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c387t-d8759a5603205673d2d05cc6da0a940605f8579d5318e9ed16188998a4581df93</citedby><cites>FETCH-LOGICAL-c387t-d8759a5603205673d2d05cc6da0a940605f8579d5318e9ed16188998a4581df93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/0895-6111(89)90076-1$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,4024,27923,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=19630142$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/2924283$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Moss, Randy H.</creatorcontrib><creatorcontrib>Stoecker, William V.</creatorcontrib><creatorcontrib>Lin, Shi-Jen</creatorcontrib><creatorcontrib>Muruganandhan, Sundararajun</creatorcontrib><creatorcontrib>Chu, Kuang-Fu</creatorcontrib><creatorcontrib>Poneleit, Kathy M.</creatorcontrib><creatorcontrib>Mitchell, Carl D.</creatorcontrib><title>Skin cancer recognition by computer vision</title><title>Computerized medical imaging and graphics</title><addtitle>Comput Med Imaging Graph</addtitle><description>Automatic detection of several features characteristic of basal cell epitheliomas is described. The features selected for this feasibility study are semitranslucency, telangiectasia, ulcer, crust, and tumor border. Image processing methods used in this study include frequency analysis of the Fourier transform of the image, the Sun-Wee texture analysis algorithm, and several other image analysis techniques suitable for skin photographs. This image analysis software is designed for use with AI/DERM, an expert system that models diagnosis of skin tumors by dermatologists.</description><subject>Artificial intelligence</subject><subject>Basal cell carcinoma (epithelioma)</subject><subject>Biological and medical sciences</subject><subject>Carcinoma, Basal Cell - diagnosis</subject><subject>Computer vision</subject><subject>Dermatology</subject><subject>Diagnosis, Differential</subject><subject>Expert Systems</subject><subject>Feasibility Studies</subject><subject>Fourier Analysis</subject><subject>Fourier Transform processing</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Image processing</subject><subject>Investigative techniques, diagnostic techniques (general aspects)</subject><subject>Medical sciences</subject><subject>Minicomputers</subject><subject>Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques</subject><subject>Pattern Recognition, Automated</subject><subject>Photography</subject><subject>Skin cancer</subject><subject>Skin Neoplasms - diagnosis</subject><subject>Skin Ulcer - diagnosis</subject><subject>Telangiectasis - diagnosis</subject><subject>Texture analysis</subject><issn>0895-6111</issn><issn>1879-0771</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1989</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kE1LAzEQhoMotVb_gcJeFBVWZ3Y3XxdBil9Q8KCeQ5pkJdru1mRb6L83tYvePA3MPPMy8xByjHCFgOwahKQ5Q8RzIS8kAGc57pAhCi5z4Bx3yfAX2ScHMX4AQAEcB2RQyKIqRDkkly-fvsmMbowLWXCmfW9859smm64z084Xyy71Vz6m1iHZq_UsuqO-jsjb_d3r-DGfPD88jW8nuSkF73IrOJWaMigLoIyXtrBAjWFWg5YVMKC1oFxaWqJw0llkKISUQldUoK1lOSJn29xFaL-WLnZq7qNxs5luXLuMigsJFdAygdUWNKGNMbhaLYKf67BWCGqjSG3-V5v_lZDqR5HCtHbS5y-nc2d_l3onaX7az3U0elaHJMfHv2zJSsCqSNzNlnNJxsq7oKLxLom0PonslG39_4d8A41Xf64</recordid><startdate>1989</startdate><enddate>1989</enddate><creator>Moss, Randy H.</creator><creator>Stoecker, William V.</creator><creator>Lin, Shi-Jen</creator><creator>Muruganandhan, Sundararajun</creator><creator>Chu, Kuang-Fu</creator><creator>Poneleit, Kathy M.</creator><creator>Mitchell, Carl D.</creator><general>Elsevier Ltd</general><general>Elsevier Science</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>1989</creationdate><title>Skin cancer recognition by computer vision</title><author>Moss, Randy H. ; Stoecker, William V. ; Lin, Shi-Jen ; Muruganandhan, Sundararajun ; Chu, Kuang-Fu ; Poneleit, Kathy M. ; Mitchell, Carl D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c387t-d8759a5603205673d2d05cc6da0a940605f8579d5318e9ed16188998a4581df93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1989</creationdate><topic>Artificial intelligence</topic><topic>Basal cell carcinoma (epithelioma)</topic><topic>Biological and medical sciences</topic><topic>Carcinoma, Basal Cell - diagnosis</topic><topic>Computer vision</topic><topic>Dermatology</topic><topic>Diagnosis, Differential</topic><topic>Expert Systems</topic><topic>Feasibility Studies</topic><topic>Fourier Analysis</topic><topic>Fourier Transform processing</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Image processing</topic><topic>Investigative techniques, diagnostic techniques (general aspects)</topic><topic>Medical sciences</topic><topic>Minicomputers</topic><topic>Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques</topic><topic>Pattern Recognition, Automated</topic><topic>Photography</topic><topic>Skin cancer</topic><topic>Skin Neoplasms - diagnosis</topic><topic>Skin Ulcer - diagnosis</topic><topic>Telangiectasis - diagnosis</topic><topic>Texture analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Moss, Randy H.</creatorcontrib><creatorcontrib>Stoecker, William V.</creatorcontrib><creatorcontrib>Lin, Shi-Jen</creatorcontrib><creatorcontrib>Muruganandhan, Sundararajun</creatorcontrib><creatorcontrib>Chu, Kuang-Fu</creatorcontrib><creatorcontrib>Poneleit, Kathy M.</creatorcontrib><creatorcontrib>Mitchell, Carl D.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Computerized medical imaging and graphics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Moss, Randy H.</au><au>Stoecker, William V.</au><au>Lin, Shi-Jen</au><au>Muruganandhan, Sundararajun</au><au>Chu, Kuang-Fu</au><au>Poneleit, Kathy M.</au><au>Mitchell, Carl D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Skin cancer recognition by computer vision</atitle><jtitle>Computerized medical imaging and graphics</jtitle><addtitle>Comput Med Imaging Graph</addtitle><date>1989</date><risdate>1989</risdate><volume>13</volume><issue>1</issue><spage>31</spage><epage>36</epage><pages>31-36</pages><issn>0895-6111</issn><eissn>1879-0771</eissn><abstract>Automatic detection of several features characteristic of basal cell epitheliomas is described. The features selected for this feasibility study are semitranslucency, telangiectasia, ulcer, crust, and tumor border. Image processing methods used in this study include frequency analysis of the Fourier transform of the image, the Sun-Wee texture analysis algorithm, and several other image analysis techniques suitable for skin photographs. This image analysis software is designed for use with AI/DERM, an expert system that models diagnosis of skin tumors by dermatologists.</abstract><cop>New York, NY</cop><pub>Elsevier Ltd</pub><pmid>2924283</pmid><doi>10.1016/0895-6111(89)90076-1</doi><tpages>6</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0895-6111 |
| ispartof | Computerized medical imaging and graphics, 1989, Vol.13 (1), p.31-36 |
| issn | 0895-6111 1879-0771 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_78904053 |
| source | MEDLINE; Elsevier ScienceDirect Journals Complete |
| subjects | Artificial intelligence Basal cell carcinoma (epithelioma) Biological and medical sciences Carcinoma, Basal Cell - diagnosis Computer vision Dermatology Diagnosis, Differential Expert Systems Feasibility Studies Fourier Analysis Fourier Transform processing Humans Image Interpretation, Computer-Assisted - methods Image processing Investigative techniques, diagnostic techniques (general aspects) Medical sciences Minicomputers Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques Pattern Recognition, Automated Photography Skin cancer Skin Neoplasms - diagnosis Skin Ulcer - diagnosis Telangiectasis - diagnosis Texture analysis |
| title | Skin cancer recognition by computer vision |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T09%3A47%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Skin%20cancer%20recognition%20by%20computer%20vision&rft.jtitle=Computerized%20medical%20imaging%20and%20graphics&rft.au=Moss,%20Randy%20H.&rft.date=1989&rft.volume=13&rft.issue=1&rft.spage=31&rft.epage=36&rft.pages=31-36&rft.issn=0895-6111&rft.eissn=1879-0771&rft_id=info:doi/10.1016/0895-6111(89)90076-1&rft_dat=%3Cproquest_cross%3E78904053%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=78904053&rft_id=info:pmid/2924283&rft_els_id=0895611189900761&rfr_iscdi=true |